Indoor 3D

The workshop Indoor 3D 2023 is the latest in the series of workshops dedicated to research and developments in the area of indoor spatial information. It aims to bring together researchers, professionals and users from the academia and industry involved in indoor mapping, 3D modeling, navigation, location-based services (LBS) and mobility. Papers addressing the following topics are welcomed (but not limited to): seamless Indoor/outdoor/underground 3D modelling, autonomous navigation in indoor/outdoor environments, Location-based services in indoor environments, indoor pedestrian tracking and trajectory prediction, disaster management in indoor/underground environments, indoor/outdoor scene understanding, machine/deep learning for indoor modelling, indoor virtual/augmented reality, indoor mobility and assistive technologies, etc. This workshop will be part of the ISPRS Geospatial Week 2023 and will be organized by the ISPRS Working Group IV/4, in cooperation with ISPRS WG IV/7.

Themes of event:

• Seamless indoor/underground/outdoor 3D modelling and mapping

• Stationary and dynamic obstacle detection

• Multisensory fusion for indoor mapping

• Eye-tracking and body sensors in indoor 3D research

• Indoor localization and route planning for disaster management

• Navigation, orientation and accessibility augmentation in indoor environments

• LBS in indoor environments

• Innovative LBS systems and applications

• Aided mobility for disabled/aged people

• Disaster prevention, analysis and management in indoor/underground environments

• Smart facility maintenance

• Spatio-temporal data modelling, analysis of movement traces

• Indoor location-linked big data

• SLAM methods in indoor environments

• Semantic parsing in indoor environments

• Visualization techniques for LBS in indoor/outdoor seamless environments

• Indoor virtual/augmented reality

• Human environment interactions in mobility context

• Multi-task collaboration for Indoor/outdoor modelling

• Indoor/outdoor scene understanding

• Machine/deep learning for indoor/outdoor modelling

• Mobility and assistive technologies

• Semantic indoor/underground/outdoor mapping

• Multimodal mobility for people with specific needs

Scientific Committee:

• Dev Raj Paudyal, University of Southern Queensland

• Berk Anbaroğlu, Geomatics Engineering Dept. of Hacettepe University

• Inger Fabris-Rotelli, University of Pretoria

• Gerhard Navratil, Technischen Universität Wien

• Kourosh Khoshelham, University of Melbourne

• Victor N. Sunday, University of Port Harcourt,

• Chenglu Wen, Xiamen University

• Yiping Chen, Sun Yat-sen University

• Ville Lehtola,  University of Twente

• Ruofei Zhong, Capital Normal University

• Yongze Song, Curtin University

• Abdoulaye Diakité, The University of New South Wales

• David  Sánchez Rodríguez, University of Las Palmas de Gran Canaria

• Pawel Boguslawski, University of the West of England (UK),

• Umit Isikdag, Mimar Sinan Fine Arts University (Turkey)

• Mohsen Kalantari, Melbourne School of Engineering

• Juntao Yang, Shandong University of Science and Technology

• Hao Cheng, Leibniz Universität Hannover

• Lei Niu, Lanzhou Jiaotong University

• Jesús Balado Frías, University of Vigo

• Bruno Vallet, LASTIG, IGN-ENSG

• Laurent Caraffa, The LASTIG lab

• Florent Geniet, The LASTIG lab

• Grégoire Grzeczkowicz, The LASTIG lab